Practical Solutions for Time Series Analysis
Introducing Darts: A New Python Library for User-Friendly Forecasting and Anomaly Detection on Time Series
Time series data, representing observations recorded sequentially over time, permeate various aspects of nature and business, from weather patterns and heartbeats to stock prices and production metrics. Efficiently processing and forecasting these data series can offer significant advantages, such as strategic business planning and anomaly detection in complex systems.
Unit8 has developed and open-sourced a new tool called Darts, aimed at simplifying time series processing and forecasting in Python. Darts aims to be the scikit-learn for time series analysis by providing a unified and consistent API, integrating various functionalities—data manipulation, model fitting, forecasting, and backtesting—into a single framework.
At the core of Darts is the TimeSeries data type, designed to represent multivariate and potentially probabilistic time series. This format ensures that time series are well-formed with a proper time index and can handle multiple samples for probabilistic models. Users can easily convert Pandas DataFrames into TimeSeries objects, facilitating seamless integration with existing data workflows.
The library supports both univariate and multivariate time series, and can generate deterministic or probabilistic forecasts. Darts also offers a wide range of built-in models, including Exponential Smoothing, (V)ARIMA, Facebook Prophet, and various deep learning models like RNNs, TCNs, and Transformers.
Darts addresses the inherent complexities of time series analysis by offering a comprehensive, unified framework that simplifies model training, forecasting, and evaluation. The ongoing development and open-source nature of Darts ensure that it will continue to evolve, incorporating new features and improvements driven by community contributions.
Value Proposition and Implementation of AI Solutions
If you want to evolve your company with AI, stay competitive, and use Darts for user-friendly forecasting and anomaly detection on time series. Discover how AI can redefine your way of work and redefine your sales processes and customer engagement.
Identify Automation Opportunities: Locate key customer interaction points that can benefit from AI.
Define KPIs: Ensure your AI endeavors have measurable impacts on business outcomes.
Select an AI Solution: Choose tools that align with your needs and provide customization.
Implement Gradually: Start with a pilot, gather data, and expand AI usage judiciously.
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Discover how AI can redefine your sales processes and customer engagement. Explore solutions at itinai.com.
